基于改进FA算法的河流突发水污染事件溯源

Source Tracing of Sudden River Pollution Based on Improved Firefly Algorithm

针对河流突发水污染事件的溯源问题,利用正向和逆向质量概率密度之间的耦合关系,实现污染源的位置、排放时间和污染源排放强度之间解耦,并结合一维水体扩散模型和美国特拉基河示踪剂实验监测数据,建立了基于改进萤火虫算法的河流突发水污染事件溯源求解方法.在求解过程中将监测数据划分为训练集和实验集,通过训练集数据利用改进的萤火虫算法对河流的水文参数进行调整,在实验集采用调整后的水文参数,并通过不同监测断面数据独立求解,通过方差分析结果,排除了溯源误差较大的监测断面数据.研究结果表明,溯源结果精度较高,并具有对监测数据的纠错能力,对实际河流突发水污染事件具有一定的指导意义.

This study is conducted to trace the source of sudden river pollution.Specifically,the coupling relationship between forward and reverse mass probability density is used to realize the decoupling of the location,discharge time,and discharge intensity of pollution sources;then,given the one-dimensional water body diffusion model and the monitoring data from the tracer experiment in Truckee River of the United States,a method for tracing the source of sudden river pollution is established on the basis of the improved firefly algorithm(FA).In the method,the monitoring data are divided into a training set and an experimental set,and by the training set data,the improved FA is employed to adjust the hydrological parameters of the river.Then,the adjusted hydrological parameters are used in the experimental set,and data from different monitoring sections are used independently for solutions.Finally,the results are analyzed by variance to exclude the data with large source-tracing errors.The results reveal that the source-tracing results have high accuracy and the ability to correct the monitoring data,which is of certain guiding significance for the actual sudden river pollution.